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elif self.transform == 'ranks':
array = array.argsort(axis=1).argsort(axis=1).astype('float')
# Use cKDTree to get distances eps to the k-th nearest neighbors for
# every sample in joint space XYZ with maximum norm
tree_xyz = spatial.cKDTree(array.T)
epsarray = tree_xyz.query(array.T, k=knn+1, p=np.inf,
eps=0., n_jobs=self.n_jobs)[0][:, knn].astype('float')
# Prepare for fast cython access
dim_x = int(np.where(xyz == 0)[0][-1] + 1)
dim_y = int(np.where(xyz == 1)[0][-1] + 1 - dim_x)
k_xz, k_yz, k_z = \
tigramite_cython_code._get_neighbors_within_eps_cython(array,
T,
dim_x,
dim_y,
epsarray,
knn,
dim)
return k_xz, k_yz, k_z